{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using PyTorch with TensorRT through ONNX:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TensorRT is a great way to take a trained PyTorch model and optimize it to run more efficiently during inference on an NVIDIA GPU.\n",
    "\n",
    "One approach to convert a PyTorch model to TensorRT is to export a PyTorch model to ONNX (an open format exchange for deep learning models) and then convert into a TensorRT engine. Essentially, we will follow this path to convert and deploy our model:\n",
    "\n",
    "![PyTorch+ONNX](./images/pytorch_onnx.png)\n",
    "\n",
    "Both TensorFlow and PyTorch models can be exported to ONNX, as well as many other frameworks. This allows models created using either framework to flow into common downstream pipelines.\n",
    "\n",
    "To get started, let's take a well-known computer vision model and follow five key steps to deploy it to the TensorRT Python runtime:\n",
    "\n",
    "1. __What format should I save my model in?__\n",
    "2. __What batch size(s) am I running inference at?__\n",
    "3. __What precision am I running inference at?__\n",
    "4. __What TensorRT path am I using to convert my model?__\n",
    "5. __What runtime am I targeting?__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. What format should I save my model in?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are going to use ResNet50, a widely used CNN architecture first described in <a href=https://arxiv.org/abs/1512.03385>this paper</a>.\n",
    "\n",
    "Let's start by loading dependencies and downloading the model. We will also move our Resnet model onto the GPU and set it to evaluation mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading: \"https://download.pytorch.org/models/resnet50-19c8e357.pth\" to /root/.cache/torch/hub/checkpoints/resnet50-19c8e357.pth\n"
     ]
    }
   ],
   "source": [
    "import torchvision.models as models\n",
    "import torch\n",
    "import torch.onnx\n",
    "\n",
    "# load the pretrained model\n",
    "resnet50 = models.resnet50(pretrained=True, progress=False).eval()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When saving a model to ONNX, PyTorch requires a test batch in proper shape and format. We pick a batch size:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "BATCH_SIZE=32\n",
    "\n",
    "dummy_input=torch.randn(BATCH_SIZE, 3, 224, 224)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we will export the model using the dummy input batch:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# export the model to ONNX\n",
    "torch.onnx.export(resnet50, dummy_input, \"resnet50_pytorch.onnx\", verbose=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that we are picking a BATCH_SIZE of 32 in this example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now Test with a Real Image:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's try a real image batch! For this example, we will simply repeat one open-source dog image from http://www.dog.ceo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(32, 224, 224, 3)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from skimage import io\n",
    "from skimage.transform import resize\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "url='https://images.dog.ceo/breeds/retriever-golden/n02099601_3004.jpg'\n",
    "img = resize(io.imread(url), (224, 224))\n",
    "img = np.expand_dims(np.array(img, dtype=np.float32), axis=0) # Expand image to have a batch dimension\n",
    "input_batch = np.array(np.repeat(img, BATCH_SIZE, axis=0), dtype=np.float32) # Repeat across the batch dimension\n",
    "\n",
    "input_batch.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f1068948880>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(input_batch[0].astype(np.float32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "resnet50_gpu = models.resnet50(pretrained=True, progress=False).to(\"cuda\").eval()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We need to move our batch onto GPU and properly format it to shape [32, 3, 224, 224]. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([32, 3, 224, 224])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_batch_chw = torch.from_numpy(input_batch).transpose(1,3).transpose(2,3)\n",
    "input_batch_gpu = input_batch_chw.to(\"cuda\")\n",
    "\n",
    "input_batch_gpu.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can run a prediction on a batch using .forward():"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(32, 1000)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with torch.no_grad():\n",
    "    predictions = np.array(resnet50_gpu(input_batch_gpu).cpu())\n",
    "\n",
    "predictions.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Verify Baseline Model Performance/Accuracy:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For a baseline, lets time our prediction in FP32:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "31.5 ms ± 72.1 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "\n",
    "with torch.no_grad():\n",
    "    preds = np.array(resnet50_gpu(input_batch_gpu).cpu())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also time FP16 precision performance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(32, 1000)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resnet50_gpu_half = resnet50_gpu.half()\n",
    "input_half = input_batch_gpu.half()\n",
    "\n",
    "with torch.no_grad():\n",
    "    preds = np.array(resnet50_gpu_half(input_half).cpu()) # Warm Up\n",
    "    \n",
    "preds.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19.4 ms ± 5.42 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "\n",
    "with torch.no_grad():\n",
    "    preds = np.array(resnet50_gpu_half(input_half).cpu())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's also make sure our results are accurate. We will look at the top 5 accuracy on a single image prediction. The image we are using is of a Golden Retriever, which is class 207 in the ImageNet dataset our model was trained on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class | Likelihood\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[(207, 13.121688),\n",
       " (208, 9.614037),\n",
       " (257, 9.361297),\n",
       " (205, 8.777787),\n",
       " (160, 8.557351)]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indices = (-predictions[0]).argsort()[:5]\n",
    "print(\"Class | Likelihood\")\n",
    "list(zip(indices, predictions[0][indices]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have a model exported to ONNX and a baseline to compare against! Let's now take our ONNX model and convert it to a TensorRT inference engine."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's restart our Jupyter Kernel so PyTorch doesn't collide with TensorRT: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "os._exit(0) # Shut down all kernels so TRT doesn't fight with PyTorch for GPU memory"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. What batch size(s) am I running inference at?\n",
    "\n",
    "We are going to run with a fixed batch size of 32 for this example. Note that above we set BATCH_SIZE to 32 when saving our model to ONNX. We need to create another dummy batch of the same size (this time it will need to be in our target precision) to test out our engine.\n",
    "\n",
    "First, as before, we will set our BATCH_SIZE to 32. Note that our trtexec command above includes the '--explicitBatch' flag to signal to TensorRT that we will be using a fixed batch size at runtime."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "BATCH_SIZE = 32"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Importantly, by default TensorRT will use the input precision you give the runtime as the default precision for the rest of the network. So before we create our new dummy batch, we also need to choose a precision as in the next section:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. What precision am I running inference at?\n",
    "\n",
    "Remember that lower precisions than FP32 tend to run faster. There are two common reduced precision modes - FP16 and INT8. Graphics cards that are designed to do inference well often have an affinity for one of these two types. This guide was developed on an NVIDIA V100, which favors FP16, so we will use that here by default. INT8 is a more complicated process that requires a calibration step.\n",
    "\n",
    "__NOTE__: Make sure you use the same precision (USE_FP16) here you saved your model in above!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "USE_FP16 = True\n",
    "target_dtype = np.float16 if USE_FP16 else np.float32"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " To create a test batch, we will once again repeat one open-source dog image from http://www.dog.ceo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(32, 224, 224, 3)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from skimage import io\n",
    "from skimage.transform import resize\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "url='https://images.dog.ceo/breeds/retriever-golden/n02099601_3004.jpg'\n",
    "img = resize(io.imread(url), (224, 224))\n",
    "input_batch = np.array(np.repeat(np.expand_dims(np.array(img, dtype=np.float32), axis=0), BATCH_SIZE, axis=0), dtype=np.float32)\n",
    "\n",
    "input_batch.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f020dc96550>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(input_batch[0].astype(np.float32))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preprocess Images:\n",
    "\n",
    "PyTorch has a normalization that it applies by default in all of its pretrained vision models - we can preprocess our images to match this normalization by the following, making sure our final result is in FP16 precision:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from torchvision.transforms import Normalize\n",
    "\n",
    "def preprocess_image(img):\n",
    "    norm = Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
    "    result = norm(torch.from_numpy(img).transpose(0,2).transpose(1,2))\n",
    "    return np.array(result, dtype=np.float16)\n",
    "\n",
    "preprocessed_images = np.array([preprocess_image(image) for image in input_batch])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. What TensorRT path am I using to convert my model?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use trtexec, a command line tool for working with TensorRT, in order to convert an ONNX model originally from PyTorch to an engine file.\n",
    "\n",
    "Let's make sure we have TensorRT installed (this comes with trtexec):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorrt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To convert the model we saved in the previous step, we need to point to the ONNX file, give trtexec a name to save the engine as, and last specify that we want to use a fixed batch size instead of a dynamic one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "&&&& RUNNING TensorRT.trtexec # trtexec --onnx=resnet50_pytorch.onnx --saveEngine=resnet_engine_pytorch.trt --explicitBatch --inputIOFormats=fp16:chw --outputIOFormats=fp16:chw --fp16\n",
      "[06/09/2021-20:23:03] [I] === Model Options ===\n",
      "[06/09/2021-20:23:03] [I] Format: ONNX\n",
      "[06/09/2021-20:23:03] [I] Model: resnet50_pytorch.onnx\n",
      "[06/09/2021-20:23:03] [I] Output:\n",
      "[06/09/2021-20:23:03] [I] === Build Options ===\n",
      "[06/09/2021-20:23:03] [I] Max batch: explicit\n",
      "[06/09/2021-20:23:03] [I] Workspace: 16 MiB\n",
      "[06/09/2021-20:23:03] [I] minTiming: 1\n",
      "[06/09/2021-20:23:03] [I] avgTiming: 8\n",
      "[06/09/2021-20:23:03] [I] Precision: FP32+FP16\n",
      "[06/09/2021-20:23:03] [I] Calibration: \n",
      "[06/09/2021-20:23:03] [I] Refit: Disabled\n",
      "[06/09/2021-20:23:03] [I] Safe mode: Disabled\n",
      "[06/09/2021-20:23:03] [I] Save engine: resnet_engine_pytorch.trt\n",
      "[06/09/2021-20:23:03] [I] Load engine: \n",
      "[06/09/2021-20:23:03] [I] Builder Cache: Enabled\n",
      "[06/09/2021-20:23:03] [I] NVTX verbosity: 0\n",
      "[06/09/2021-20:23:03] [I] Tactic sources: Using default tactic sources\n",
      "[06/09/2021-20:23:03] [I] Input(s): fp16:chw\n",
      "[06/09/2021-20:23:03] [I] Output(s): fp16:chw\n",
      "[06/09/2021-20:23:03] [I] Input build shapes: model\n",
      "[06/09/2021-20:23:03] [I] Input calibration shapes: model\n",
      "[06/09/2021-20:23:03] [I] === System Options ===\n",
      "[06/09/2021-20:23:03] [I] Device: 0\n",
      "[06/09/2021-20:23:03] [I] DLACore: \n",
      "[06/09/2021-20:23:03] [I] Plugins:\n",
      "[06/09/2021-20:23:03] [I] === Inference Options ===\n",
      "[06/09/2021-20:23:03] [I] Batch: Explicit\n",
      "[06/09/2021-20:23:03] [I] Input inference shapes: model\n",
      "[06/09/2021-20:23:03] [I] Iterations: 10\n",
      "[06/09/2021-20:23:03] [I] Duration: 3s (+ 200ms warm up)\n",
      "[06/09/2021-20:23:03] [I] Sleep time: 0ms\n",
      "[06/09/2021-20:23:03] [I] Streams: 1\n",
      "[06/09/2021-20:23:03] [I] ExposeDMA: Disabled\n",
      "[06/09/2021-20:23:03] [I] Data transfers: Enabled\n",
      "[06/09/2021-20:23:03] [I] Spin-wait: Disabled\n",
      "[06/09/2021-20:23:03] [I] Multithreading: Disabled\n",
      "[06/09/2021-20:23:03] [I] CUDA Graph: Disabled\n",
      "[06/09/2021-20:23:03] [I] Separate profiling: Disabled\n",
      "[06/09/2021-20:23:03] [I] Skip inference: Disabled\n",
      "[06/09/2021-20:23:03] [I] Inputs:\n",
      "[06/09/2021-20:23:03] [I] === Reporting Options ===\n",
      "[06/09/2021-20:23:03] [I] Verbose: Disabled\n",
      "[06/09/2021-20:23:03] [I] Averages: 10 inferences\n",
      "[06/09/2021-20:23:03] [I] Percentile: 99\n",
      "[06/09/2021-20:23:03] [I] Dump refittable layers:Disabled\n",
      "[06/09/2021-20:23:03] [I] Dump output: Disabled\n",
      "[06/09/2021-20:23:03] [I] Profile: Disabled\n",
      "[06/09/2021-20:23:03] [I] Export timing to JSON file: \n",
      "[06/09/2021-20:23:03] [I] Export output to JSON file: \n",
      "[06/09/2021-20:23:03] [I] Export profile to JSON file: \n",
      "[06/09/2021-20:23:03] [I] \n",
      "[06/09/2021-20:23:04] [I] === Device Information ===\n",
      "[06/09/2021-20:23:04] [I] Selected Device: Tesla V100-DGXS-16GB\n",
      "[06/09/2021-20:23:04] [I] Compute Capability: 7.0\n",
      "[06/09/2021-20:23:04] [I] SMs: 80\n",
      "[06/09/2021-20:23:04] [I] Compute Clock Rate: 1.53 GHz\n",
      "[06/09/2021-20:23:04] [I] Device Global Memory: 16155 MiB\n",
      "[06/09/2021-20:23:04] [I] Shared Memory per SM: 96 KiB\n",
      "[06/09/2021-20:23:04] [I] Memory Bus Width: 4096 bits (ECC enabled)\n",
      "[06/09/2021-20:23:04] [I] Memory Clock Rate: 0.877 GHz\n",
      "[06/09/2021-20:23:04] [I] \n",
      "[06/09/2021-20:23:20] [I] [TRT] ----------------------------------------------------------------\n",
      "[06/09/2021-20:23:20] [I] [TRT] Input filename:   resnet50_pytorch.onnx\n",
      "[06/09/2021-20:23:20] [I] [TRT] ONNX IR version:  0.0.6\n",
      "[06/09/2021-20:23:20] [I] [TRT] Opset version:    9\n",
      "[06/09/2021-20:23:20] [I] [TRT] Producer name:    pytorch\n",
      "[06/09/2021-20:23:20] [I] [TRT] Producer version: 1.9\n",
      "[06/09/2021-20:23:20] [I] [TRT] Domain:           \n",
      "[06/09/2021-20:23:20] [I] [TRT] Model version:    0\n",
      "[06/09/2021-20:23:20] [I] [TRT] Doc string:       \n",
      "[06/09/2021-20:23:20] [I] [TRT] ----------------------------------------------------------------\n",
      "[06/09/2021-20:23:24] [I] [TRT] Some tactics do not have sufficient workspace memory to run. Increasing workspace size may increase performance, please check verbose output.\n",
      "[06/09/2021-20:24:49] [I] [TRT] Detected 1 inputs and 1 output network tensors.\n",
      "[06/09/2021-20:24:49] [I] Engine built in 105.672 sec.\n",
      "[06/09/2021-20:24:50] [I] Starting inference\n",
      "[06/09/2021-20:24:53] [I] Warmup completed 0 queries over 200 ms\n",
      "[06/09/2021-20:24:53] [I] Timing trace has 0 queries over 2.9909 s\n",
      "[06/09/2021-20:24:53] [I] Trace averages of 10 runs:\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.35326 ms - Host latency: 6.18286 ms (end to end 10.1932 ms, enqueue 0.460231 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.35654 ms - Host latency: 6.19131 ms (end to end 10.2018 ms, enqueue 0.473865 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.38982 ms - Host latency: 6.22551 ms (end to end 10.2071 ms, enqueue 0.460098 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.3761 ms - Host latency: 6.24244 ms (end to end 10.2638 ms, enqueue 0.456512 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.36218 ms - Host latency: 6.22775 ms (end to end 9.37773 ms, enqueue 0.441846 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.35991 ms - Host latency: 6.22073 ms (end to end 9.77996 ms, enqueue 0.443829 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.38082 ms - Host latency: 6.25148 ms (end to end 10.0299 ms, enqueue 0.44693 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.39341 ms - Host latency: 6.26748 ms (end to end 10.0738 ms, enqueue 0.456384 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.38766 ms - Host latency: 6.26089 ms (end to end 10.2009 ms, enqueue 0.461377 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.37385 ms - Host latency: 6.24359 ms (end to end 9.65547 ms, enqueue 0.442078 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.35819 ms - Host latency: 6.21615 ms (end to end 8.21369 ms, enqueue 0.436646 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.34844 ms - Host latency: 6.20999 ms (end to end 9.77367 ms, enqueue 0.433765 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.35132 ms - Host latency: 6.21758 ms (end to end 10.6213 ms, enqueue 0.435864 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.36421 ms - Host latency: 6.23065 ms (end to end 10.5457 ms, enqueue 0.436438 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.39054 ms - Host latency: 6.25834 ms (end to end 10.4534 ms, enqueue 0.444727 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.36874 ms - Host latency: 6.23105 ms (end to end 8.89895 ms, enqueue 0.443665 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.35729 ms - Host latency: 6.21859 ms (end to end 8.51741 ms, enqueue 0.437866 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.33851 ms - Host latency: 6.19753 ms (end to end 9.1334 ms, enqueue 0.438574 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.34199 ms - Host latency: 6.21041 ms (end to end 10.6064 ms, enqueue 0.44613 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.33002 ms - Host latency: 6.20233 ms (end to end 10.5858 ms, enqueue 0.458911 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.38256 ms - Host latency: 6.25411 ms (end to end 9.77722 ms, enqueue 0.460205 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.3837 ms - Host latency: 6.2543 ms (end to end 9.4882 ms, enqueue 0.448364 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.35146 ms - Host latency: 6.20986 ms (end to end 8.36691 ms, enqueue 0.434412 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.34351 ms - Host latency: 6.20732 ms (end to end 10.1922 ms, enqueue 0.439209 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.3502 ms - Host latency: 6.21951 ms (end to end 10.6236 ms, enqueue 0.451489 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.34368 ms - Host latency: 6.21904 ms (end to end 10.4949 ms, enqueue 0.462231 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.33777 ms - Host latency: 6.21189 ms (end to end 9.99021 ms, enqueue 0.455859 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.33193 ms - Host latency: 6.19707 ms (end to end 9.02058 ms, enqueue 0.445972 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.33115 ms - Host latency: 6.19114 ms (end to end 9.11257 ms, enqueue 0.433862 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.34673 ms - Host latency: 6.21465 ms (end to end 10.6074 ms, enqueue 0.442139 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.38572 ms - Host latency: 6.25532 ms (end to end 10.3253 ms, enqueue 0.446631 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.36335 ms - Host latency: 6.23845 ms (end to end 10.6406 ms, enqueue 0.45625 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.36877 ms - Host latency: 6.24153 ms (end to end 10.2023 ms, enqueue 0.449341 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.36023 ms - Host latency: 6.21748 ms (end to end 8.45557 ms, enqueue 0.436719 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.34392 ms - Host latency: 6.20728 ms (end to end 10.1899 ms, enqueue 0.438428 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.34636 ms - Host latency: 6.21821 ms (end to end 10.6184 ms, enqueue 0.447217 ms)\n",
      "[06/09/2021-20:24:53] [I] Average on 10 runs - GPU latency: 5.33555 ms - Host latency: 6.20952 ms (end to end 10.5899 ms, enqueue 0.459546 ms)\n",
      "[06/09/2021-20:24:53] [I] Host Latency\n",
      "[06/09/2021-20:24:53] [I] min: 6.16092 ms (end to end 6.17383 ms)\n",
      "[06/09/2021-20:24:53] [I] max: 6.2887 ms (end to end 10.8184 ms)\n",
      "[06/09/2021-20:24:53] [I] mean: 6.22352 ms (end to end 9.90214 ms)\n",
      "[06/09/2021-20:24:53] [I] median: 6.22021 ms (end to end 10.6108 ms)\n",
      "[06/09/2021-20:24:53] [I] percentile: 6.28583 ms at 99% (end to end 10.7902 ms at 99%)\n",
      "[06/09/2021-20:24:53] [I] throughput: 0 qps\n",
      "[06/09/2021-20:24:53] [I] walltime: 2.9909 s\n",
      "[06/09/2021-20:24:53] [I] Enqueue Time\n",
      "[06/09/2021-20:24:53] [I] min: 0.424072 ms\n",
      "[06/09/2021-20:24:53] [I] max: 0.49585 ms\n",
      "[06/09/2021-20:24:53] [I] median: 0.445618 ms\n",
      "[06/09/2021-20:24:53] [I] GPU Compute\n",
      "[06/09/2021-20:24:53] [I] min: 5.30127 ms\n",
      "[06/09/2021-20:24:53] [I] max: 5.42108 ms\n",
      "[06/09/2021-20:24:53] [I] mean: 5.35895 ms\n",
      "[06/09/2021-20:24:53] [I] median: 5.35571 ms\n",
      "[06/09/2021-20:24:53] [I] percentile: 5.41693 ms at 99%\n",
      "[06/09/2021-20:24:53] [I] total compute time: 2.00961 s\n",
      "&&&& PASSED TensorRT.trtexec # trtexec --onnx=resnet50_pytorch.onnx --saveEngine=resnet_engine_pytorch.trt --explicitBatch --inputIOFormats=fp16:chw --outputIOFormats=fp16:chw --fp16\n"
     ]
    }
   ],
   "source": [
    "# step out of Python for a moment to convert the ONNX model to a TRT engine using trtexec\n",
    "if USE_FP16:\n",
    "    !trtexec --onnx=resnet50_pytorch.onnx --saveEngine=resnet_engine_pytorch.trt  --explicitBatch --inputIOFormats=fp16:chw --outputIOFormats=fp16:chw --fp16\n",
    "else:\n",
    "    !trtexec --onnx=resnet50_pytorch.onnx --saveEngine=resnet_engine_pytorch.trt  --explicitBatch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This will save our model as 'resnet_engine.trt'."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. What TensorRT runtime am I targeting?\n",
    "\n",
    "Now, we have a converted our model to a TensorRT engine. Great! That means we are ready to load it into the native Python TensorRT runtime. This runtime strikes a balance between the ease of use of the high level Python APIs used in frameworks and the fast, low level C++ runtimes available in TensorRT."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 15.9 s, sys: 556 ms, total: 16.5 s\n",
      "Wall time: 19.3 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "import tensorrt as trt\n",
    "import pycuda.driver as cuda\n",
    "import pycuda.autoinit\n",
    "\n",
    "f = open(\"resnet_engine_pytorch.trt\", \"rb\")\n",
    "runtime = trt.Runtime(trt.Logger(trt.Logger.WARNING)) \n",
    "\n",
    "engine = runtime.deserialize_cuda_engine(f.read())\n",
    "context = engine.create_execution_context()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now allocate input and output memory, give TRT pointers (bindings) to it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "# need to set input and output precisions to FP16 to fully enable it\n",
    "output = np.empty([BATCH_SIZE, 1000], dtype = target_dtype) \n",
    "\n",
    "# allocate device memory\n",
    "d_input = cuda.mem_alloc(1 * input_batch.nbytes)\n",
    "d_output = cuda.mem_alloc(1 * output.nbytes)\n",
    "\n",
    "bindings = [int(d_input), int(d_output)]\n",
    "\n",
    "stream = cuda.Stream()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, set up the prediction function.\n",
    "\n",
    "This involves a copy from CPU RAM to GPU VRAM, executing the model, then copying the results back from GPU VRAM to CPU RAM:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict(batch): # result gets copied into output\n",
    "    # transfer input data to device\n",
    "    cuda.memcpy_htod_async(d_input, batch, stream)\n",
    "    # execute model\n",
    "    context.execute_async_v2(bindings, stream.handle, None)\n",
    "    # transfer predictions back\n",
    "    cuda.memcpy_dtoh_async(output, d_output, stream)\n",
    "    # syncronize threads\n",
    "    stream.synchronize()\n",
    "    \n",
    "    return output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's time the function!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warming up...\n",
      "Done warming up!\n"
     ]
    }
   ],
   "source": [
    "print(\"Warming up...\")\n",
    "\n",
    "pred = predict(preprocessed_images)\n",
    "\n",
    "print(\"Done warming up!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6.28 ms ± 1.07 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "\n",
    "pred = predict(preprocessed_images)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally we should verify our TensorRT output is still accurate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class | Probability (out of 1)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[(207, 12.44), (208, 7.508), (220, 7.492), (160, 7.426), (226, 7.383)]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indices = (-pred[0]).argsort()[:5]\n",
    "print(\"Class | Probability (out of 1)\")\n",
    "list(zip(indices, pred[0][indices]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Look for ImageNet indices 150-275 above, where 207 is the ground truth correct class (Golden Retriever). Compare with the results of the original unoptimized model in the first section!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Next Steps:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4> Profiling </h4>\n",
    "\n",
    "This is a great next step for further optimizing and debugging models you are working on productionizing\n",
    "\n",
    "You can find it here: https://docs.nvidia.com/deeplearning/tensorrt/best-practices/index.html\n",
    "\n",
    "<h4>  TRT Dev Docs </h4>\n",
    "\n",
    "Main documentation page for the ONNX, layer builder, C++, and legacy APIs\n",
    "\n",
    "You can find it here: https://docs.nvidia.com/deeplearning/tensorrt/developer-guide/index.html\n",
    "\n",
    "<h4>  TRT OSS GitHub </h4>\n",
    "\n",
    "Contains OSS TRT components, sample applications, and plugin examples\n",
    "\n",
    "You can find it here: https://github.com/NVIDIA/TensorRT\n",
    "\n",
    "\n",
    "#### TRT Supported Layers:\n",
    "\n",
    "https://github.com/NVIDIA/TensorRT/tree/master/samples/opensource/samplePlugin\n",
    "\n",
    "#### TRT ONNX Plugin Example:\n",
    "\n",
    "https://docs.nvidia.com/deeplearning/tensorrt/support-matrix/index.html#layers-precision-matrix"
   ]
  }
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